Title: Innovative research on encryption and protection of e-commerce with big data analysis

Authors: Yifu Shu; Wenda Wang

Addresses: School of Mathematics and Statistics, University of Glasgow, Scotland, G12 8QQ, UK ' School of Computing Science, University of Glasgow, Scotland, G12 8QQ, UK

Abstract: In the e-commerce sector, protecting data privacy is crucial. This study introduces the symmetric balanced funnel Pˆ5 model as a method for addressing data protection challenges. The Pˆ5 model organises data protection into five levels, each tailored to the specific security needs of different types of e-commerce data. It employs encryption algorithms like DES, AES, and RSA, with increasing encryption strength across the levels to ensure adequate protection. This approach not only safeguards user confidentiality and commercial interests but also provides balanced protection for data exchanged between parties. By offering focused protection for various categories of sensitive data, the Pˆ5 model enhances overall data security in e-commerce. This study offers a new and comprehensive strategy for ensuring data privacy in e-commerce environments.

Keywords: big data security; e-commerce data; symmetric balanced funnel Pˆ5; multilevel encryption; data privacy; cybersecurity.

DOI: 10.1504/IJDS.2024.139805

International Journal of Data Science, 2024 Vol.9 No.2, pp.123 - 142

Received: 17 Aug 2023
Accepted: 17 Dec 2023
Published online: 05 Jul 2024 *

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